[R] Selecting a minimum value of an attribute associated with point values neighboring a given point and assigning it as a new attribute

[Bert Gunter]

Probably better posted on R-sig-geo.

-- Bert

On Sat, Nov 5, 2022 at 12:36 AM Duhl, Tiffany R. <Tiffany.Duhl using tufts.edu>
wrote:

> Hello,
>
> I have sets of spatial points with LAT, LON coords (unprojected, WGS84
> datum) and several value attributes associated with each point, from
> numerous csv files (with an average of 6,000-9,000 points in each file) as
> shown in the following example:
>
> data<- read.csv("R_find_pts_testdata.csv")
>
> > data
>     ID      Date         Time        LAT            LON           Conc
> Leg.Speed    CO2  H2O BC61 Hr Min Sec
> 1   76 4/19/2021 21:25:38 42.40066 -70.98802 99300   0.0 mph 428.39 9.57
> 578 21  25  38
> 2   77 4/19/2021 21:25:39 42.40066 -70.98802 96730   0.0 mph 428.04 9.57
> 617 21  25  39
> 3   79 4/19/2021 21:25:41 42.40066 -70.98802 98800   0.2 mph 427.10 9.57
> 1027 21  25  41
> 4   80 4/19/2021 21:25:42 42.40066 -70.98802 96510     2 mph 427.99 9.58
> 1381 21  25  42
> 5   81 4/19/2021 21:25:43 42.40067 -70.98801 95540     3 mph 427.99 9.58
> 1271 21  25  43
> 6   82 4/19/2021 21:25:44 42.40068 -70.98799 94720     4 mph 427.20 9.57
> 910 21  25  44
> 7   83 4/19/2021 21:25:45 42.40069 -70.98797 94040     5 mph 427.18 9.57
> 652 21  25  45
> 8   84 4/19/2021 21:25:46 42.40072 -70.98795 95710     7 mph 427.07 9.57
> 943 21  25  46
> 9   85 4/19/2021 21:25:47 42.40074 -70.98792 96200     8 mph 427.44 9.56
> 650 21  25  47
> 10  86 4/19/2021 21:25:48 42.40078 -70.98789 93750    10 mph 428.76 9.57
> 761 21  25  48
> 11  87 4/19/2021 21:25:49 42.40081 -70.98785 93360    11 mph 429.25 9.56
> 1158 21  25  49
> 12  88 4/19/2021 21:25:50 42.40084 -70.98781 94340    12 mph 429.56 9.57
> 107 21  25  50
> 13  89 4/19/2021 21:25:51 42.40087 -70.98775 92780    12 mph 428.62 9.56
> 720 21  25  51
>
>
> What I want to do is, for each point, identify all points within 50m of
> that point, find the minimum value of the "Conc" attribute of each nearby
> set of points (including the original point) and then create a new variable
> ("Conc_min") and assign this minimum value to a new variable added to
> "data".
>
> So far, I have the following code:
>
> library(spdep)
> library(sf)
>
> setwd("C:\\mydirectory\\")
> data<- read.csv("R_find_pts_testdata.csv")
>
> #make sure the data is a data frame
> pts <- data.frame(data)
>
> #create spatial data frame and define projection
> pts_coords <- cbind(pts$LON, pts$LAT)
> data_pts <- SpatialPointsDataFrame(coords= pts_coords,
> data=pts, proj4string = CRS("+proj=longlat +datum=WGS84"))
>
> #Re-project to WGS 84 / UTM zone 18N, so the analysis is in units of m
> ptsUTM  <- sf::st_as_sf(data_pts, coords = c("LAT", "LON"), remove = F)%>%
> st_transform(32618)
>
> #create 50 m buffer around each point then intersect with points and
> finally find neighbors within the buffers
> pts_buf <- sf::st_buffer(ptsUTM, 50)
> coords  <- sf::st_coordinates(ptsUTM)
> int <- sf::st_intersects(pts_buf, ptsUTM)
> x   <- spdep::dnearneigh(coords, 0, 50)
>
> Now at this point, I'm not sure what to either the "int" (a sgbp list) or
> "x" (nb object) objects (or even if I need them both)
>
> > int
> Sparse geometry binary predicate list of length 974, where the predicate
> was `intersects'
> first 10 elements:
>  1: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
>  2: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
>  3: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
>  4: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
>  5: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
>  6: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
>  7: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
>  8: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
>  9: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
>
> > x
> Neighbour list object:
> Number of regions: 974
> Number of nonzero links: 34802
> Percentage nonzero weights: 3.668481
> Average number of links: 35.73101
>
> One thought is that maybe I don't need the dnearneigh function and can
> instead convert "int" into a dataframe and somehow merge or associate
> (perhaps with an inner join) the ID fields of the buffered and intersecting
> points and then compute the minimum value of "Conc" grouping by ID:
>
> > as.data.frame(int)
>     row.id col.id
> 1        1      1
> 2        1      2
> 3        1      3
> 4        1      4
> 5        1      5
> 6        1      6
> 7        1      7
> 8        1      8
> 9        1      9
> 10       1     10
> 11       1     11
> 12       1     12
> 13       1     13
> 14       1     14
> 15       1     15
> 16       1     16
> 17       1     17
> 18       1     18
> 19       2      1
> 20       2      2
> 21       2      3
> 22       2      4
> 23       2      5
> 24       2      6
> 25       2      7
> 26       2      8
> 27       2      9
> 28       2     10
>
>
> So in the above example I'd like to take the minimum of "Conc" among the
> col.id points grouped with row.id 1 (i.e., col.ids 1-18) and assign the
> minimum value of this group as a new variable in data (Data$Conc_min), and
> do the same for row.id 2 and all the rest of the rows.
>
> I'm just not sure how to do this and I appreciate any help folks might
> have on this matter!
>
> Many thanks,
> -Tiffany
>
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>
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